Compared to a conventional mono-facial photovoltaic (PV) module, a bifacial one is more efficient as it receives light from not only the front but also the backside. The daily irradiance profile of a bifacial PV module is of a two-peak trajectory that almost coincides with the morning and evening peak demands. This interesting property helps distribution network operators better handle the issues caused by the abundance of conventional PVs during midday (i.e., Duck curve). Moreover, this two-humped profile can be incorporated into network operation strategies such as conservation voltage reduction (CVR). Thus, this paper proposes a new CVR framework that best uses the double-peak profile of bifacial PV modules to improve the voltage profile of a distribution network. The proposed framework optimally coordinates legacy voltage control devices, including on-load tap changers and voltage regulators, as well as Volt/VAr control of smart inverters. The effectiveness of the proposed framework is simulated and verified on the well-known modified 34-bus system using the Matlab-COM-OpenDSS platform. The results clearly demonstrate the advantages of bifacial PVs over their mono-facial counterparts.
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Implementation of CVR in Distribution Networks by Optimal Coordination of BESS and PV Inverters Using Arithmetic Optimization Algorithm
This article proposes a new framework for the substation demand reduction and power loss minimization in distribution networks by implementing conservation voltage reduction (CVR) strategy. The proposed framework coordinates Battery Energy Storage Systems (BESS), Smart PV inverters and voltage control devices -including OLTC and voltage regulators- so that the substation demand and network power loss are reduced while the service voltage range meets the IEEE 1547 standard (120-114 V). The suggested CVR
strategy is applied to the IEEE 34-bus case study system consisting of two PV generations and BESS. The smart PV inverters are controlled based on the combined Volt/VArVolt/Watt (VVW) characteristics scheme. Also, BESS is charged and discharged with regard to the time and peaks have control modes, respectively. The Arithmetic Optimization Algorithm (AOA) is implemented in MATLAB scripts for solving the optimization problem. Power flow studies are carried out using OpenDSS software. Results reveal that the new framework can achieve higher substation demand reduction considering the concurrent control of PVs and BESS.
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- Award ID(s):
- 1939144
- NSF-PAR ID:
- 10317607
- Date Published:
- Journal Name:
- IEEE Green Technologies Conference (GreenTech)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/NAPS52732.2021.9654489
